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<a name="details" id="details"></a><h2 class="groupheader"> </h2>
<p>Loss functions define loss values between a model prediction and a given label. </p>
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Classes</h2></td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_abstract_loss.html">shark::AbstractLoss&lt; LabelT, OutputT &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Loss function interface.  <a href="classshark_1_1_abstract_loss.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_cross_entropy.html">shark::CrossEntropy&lt; LabelType, OutputType &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Error measure for classification tasks that can be used as the objective function for training.  <a href="classshark_1_1_cross_entropy.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_discrete_loss.html">shark::DiscreteLoss</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">flexible loss for classification  <a href="classshark_1_1_discrete_loss.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_epsilon_hinge_loss.html">shark::EpsilonHingeLoss</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Hinge-loss for large margin regression.  <a href="classshark_1_1_epsilon_hinge_loss.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_hinge_loss.html">shark::HingeLoss</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Hinge-loss for large margin classification.  <a href="classshark_1_1_hinge_loss.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_huber_loss.html">shark::HuberLoss</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Huber-loss for for robust regression.  <a href="classshark_1_1_huber_loss.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_squared_epsilon_hinge_loss.html">shark::SquaredEpsilonHingeLoss</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Hinge-loss for large margin regression using th squared two-norm.  <a href="classshark_1_1_squared_epsilon_hinge_loss.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_squared_hinge_loss.html">shark::SquaredHingeLoss</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Squared Hinge-loss for large margin classification.  <a href="classshark_1_1_squared_hinge_loss.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_squared_loss.html">shark::SquaredLoss&lt; OutputType, LabelType &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">squared loss for regression and classification  <a href="classshark_1_1_squared_loss.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_zero_one_loss.html">shark::ZeroOneLoss&lt; LabelType, OutputType &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">0-1-loss for classification.  <a href="classshark_1_1_zero_one_loss.html#details">More...</a><br /></td></tr>
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